# Following codebook package's [vignette](https://cran.r-project.org/web/packages/codebook/vignettes/codebook_tutorial.html)
# Dependencies
library(tidyverse)
library(knitr)
library(kableExtra)
library(codebook)
library(labelled)
library(rio)
# Add labels ----
# read data
data_codebook <- read.csv("processed/4_data_participant_level_with_hand_scoring.csv")
# read data data_dictionary
data_dictionary <- read.csv("processed/5_data_dictionary.csv")
# add data_dictionary as labels
var_label(data_codebook) <- data_dictionary %>%
select(variable, label) %>%
dict_to_list()
# Add meta data ----
metadata(data_codebook)$name <- "Evaluative learning via deepfaked media"
metadata(data_codebook)$description <- "Across multiple experiments, we demonstrated that 'deepfakes' can establish automatic biases, self-reported evaluations, and behavioural intentions."
#metadata(data_codebook)$identifier <- "https://dx.doi.org/XXXXXXX"
metadata(data_codebook)$creator <- "Sean Hughes"
metadata(data_codebook)$citation <- "Hughes, S., Fried, O., Ferguson, M. J., Yao, D., Hughes, C., Hughes, R., & Hussey, I. (2020). Using Deepfakes to Hack the Human Mind."
metadata(data_codebook)$url <- "https://github.com/Sean-Hughes/DF-Impression-Formation--Video-and-Audio-"
# other meta data: see https://schema.org/Dataset
metadata(data_codebook)$datePublished <- "2020"
metadata(data_codebook)$spatialCoverage <- "Online"
# Create codebook ----
data_codebook %>%
select(-behavioral_intentions_share, -behavioral_intentions_subscribe, -behavioral_intentions_recommend) %>%
codebook()Dataset name: .
The dataset has N=1730 rows and 76 columns. 0 rows have no missing values on any column.
Metadata for search engines
|
#Variables
Unique subject identifier
Distribution of values for subject
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| subject | Unique subject identifier | character | 0 | 1 | 1730 | 0 | 36 | 36 | 0 |
Experiment data was collected as part of
Distribution of values for experiment
0 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| experiment | Experiment data was collected as part of | numeric | 0 | 1 | 1 | 4 | 6 | 3.739306 | 1.482387 | ▆▇▇▅▅ |
What medium did the intervention (whether deepfaked or genuine) take (e.g. video and audio vs just audio)
Distribution of values for intervention_medium
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| intervention_medium | What medium did the intervention (whether deepfaked or genuine) take (e.g. video and audio vs just audio) | character | 0 | 1 | 2 | 0 | 5 | 5 | 0 |
What was the researcher-intended valence of the intervention? I.e. was the participant exposed to positive or negative messages?
Distribution of values for source_valence
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| source_valence | What was the researcher-intended valence of the intervention? I.e. was the participant exposed to positive or negative messages? | character | 0 | 1 | 2 | 0 | 8 | 8 | 0 |
Was the intervention genuine or deepfaked content?
Distribution of values for experiment_condition
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| experiment_condition | Was the intervention genuine or deepfaked content? | character | 0 | 1 | 2 | 0 | 7 | 9 | 0 |
Should the participant be excluded (TRUE) or retained (FALSE) based on passed_iat_performance complete_iat complete_selfreport and complete_intentions
Distribution of values for exclude_subject
0 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| exclude_subject | Should the participant be excluded (TRUE) or retained (FALSE) based on passed_iat_performance complete_iat complete_selfreport and complete_intentions | logical | 0 | 1 | FAL: 1421, TRU: 309 | 0.1786127 |
Should the participant be excluded (TRUE) or retained (FALSE) based on them spending not enough time (<1.5 minutes or too much time (>4.5 minutes) on the page that delivered the audio/video intervention.
Distribution of values for exclude_implausible_intervention_linger
55 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| exclude_implausible_intervention_linger | Should the participant be excluded (TRUE) or retained (FALSE) based on them spending not enough time (<1.5 minutes or too much time (>4.5 minutes) on the page that delivered the audio/video intervention. | logical | 55 | 0.9682081 | FAL: 1555, TRU: 120 | 0.0716418 |
Number of minutes spent viewing the page that delivered the intervention.
Distribution of values for intervention_linger_minutes
55 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| intervention_linger_minutes | Number of minutes spent viewing the page that delivered the intervention. | numeric | 55 | 0.9682081 | 0.028 | 2.7 | 2.7e+07 | 31805.05 | 920066.9 | ▇▁▁▁▁ |
Participant age
Distribution of values for age
0 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| age | Participant age | numeric | 0 | 1 | 18 | 29 | 70 | 31.24335 | 9.94172 | ▇▆▃▁▁ |
Participant gender
Distribution of values for gender
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| gender | Participant gender | character | 0 | 1 | 5 | 0 | 4 | 22 | 0 |
The IAT captures automatic evaluations of Chris the character depicted in the intervention. Accuracies and reaction times on IAT were converted to D2 scores following Greenwald et al 2003 and implemented using the IATScores R package. Briefly D2 is a standardized difference score of trimmed reaction times in one block type versus the other: (mean_block_2 - mean_block_1) / standard_deviation_all_blocks
Distribution of values for IAT_D2
141 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| IAT_D2 | The IAT captures automatic evaluations of Chris the character depicted in the intervention. Accuracies and reaction times on IAT were converted to D2 scores following Greenwald et al 2003 and implemented using the IATScores R package. Briefly D2 is a standardized difference score of trimmed reaction times in one block type versus the other: (mean_block_2 - mean_block_1) / standard_deviation_all_blocks | numeric | 141 | 0.9184971 | -1.2 | 0.23 | 1.6 | 0.2084644 | 0.3642037 | ▁▃▇▃▁ |
Mean self-reported evaluation (positive-negative good-bad pleasant-unpleasant) of Chris the character depicted in the intervention.
Distribution of values for mean_self_reported_evaluation
98 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| mean_self_reported_evaluation | Mean self-reported evaluation (positive-negative good-bad pleasant-unpleasant) of Chris the character depicted in the intervention. | numeric | 98 | 0.9433526 | -3 | 0 | 3 | -0.0859804 | 2.029025 | ▇▃▃▅▇ |
Mean behavioural intentions
Distribution of values for mean_intentions
1485 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| mean_intentions | Mean behavioural intentions | numeric | 1485 | 0.1416185 | -2 | -1 | 2 | -0.9239184 | 1.052152 | ▇▅▃▂▁ |
Open ended responses to the deepfaking detection question were hand scored by two independent reviewers (see “3 Instructions for raters.docx”). If both reviewers scored an open ended response as having detected the intervention as a deepfake (whether correctly or not), this variable was set to TRUE. Otherwise FALSE.
Distribution of values for deepfake_detected
1120 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| deepfake_detected | Open ended responses to the deepfaking detection question were hand scored by two independent reviewers (see “3 Instructions for raters.docx”). If both reviewers scored an open ended response as having detected the intervention as a deepfake (whether correctly or not), this variable was set to TRUE. Otherwise FALSE. | logical | 1120 | 0.3526012 | FAL: 493, TRU: 117 | 0.1918033 |
Item level data for self report ratings scale item 1, bad vs good
Distribution of values for ratings_bad_good
98 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ratings_bad_good | Item level data for self report ratings scale item 1, bad vs good | numeric | 98 | 0.9433526 | -3 | 0 | 3 | -0.0759804 | 2.036241 | ▇▂▃▃▇ |
Item level data for self report ratings scale item 1, dislike vs like
Distribution of values for ratings_dislike_like
98 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ratings_dislike_like | Item level data for self report ratings scale item 1, dislike vs like | numeric | 98 | 0.9433526 | -3 | 0 | 3 | -0.0900735 | 2.071641 | ▇▂▃▃▇ |
Item level data for self report ratings scale item 1, negative vs positive
Distribution of values for ratings_negative_positive
98 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ratings_negative_positive | Item level data for self report ratings scale item 1, negative vs positive | numeric | 98 | 0.9433526 | -3 | 0 | 3 | -0.0919118 | 2.058646 | ▇▂▃▃▇ |
Question assessing whether people believe that the targets actions in the video/audio were representative of his ‘true’ character
Distribution of values for diagnosticity
70 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| diagnosticity | Question assessing whether people believe that the targets actions in the video/audio were representative of his ‘true’ character | numeric | 70 | 0.9595376 | 0 | 2 | 3 | 1.966867 | 0.7643258 | ▁▃▁▇▃ |
Assesssment of whether evaluations of the targer reflected how the person genuinely felt or if they simply responded in a way they thought the researchers wanted them to.
Distribution of values for demand
131 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| demand | Assesssment of whether evaluations of the targer reflected how the person genuinely felt or if they simply responded in a way they thought the researchers wanted them to. | logical | 131 | 0.9242775 | FAL: 1585, TRU: 14 | 0.0087555 |
Assesssment of whether evaluations of the targer reflected how the person genuinely felt or if they responded in the opposite way than they thought the researchers wanted them to.
Distribution of values for reactance
131 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| reactance | Assesssment of whether evaluations of the targer reflected how the person genuinely felt or if they responded in the opposite way than they thought the researchers wanted them to. | logical | 131 | 0.9242775 | FAL: 1537, TRU: 62 | 0.0387742 |
Question asking what participants thought the experiment was about (i.e. what the experimenter’s agenda was in the study)
Distribution of values for hypothesis_awareness
1672 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| hypothesis_awareness | Question asking what participants thought the experiment was about (i.e. what the experimenter’s agenda was in the study) | logical | 1672 | 0.033526 | FAL: 58 | 0 |
Question asking if participants thought the video/audio influenced how much they liked or disliked the target
Distribution of values for influence_awareness
946 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| influence_awareness | Question asking if participants thought the video/audio influenced how much they liked or disliked the target | logical | 946 | 0.4531792 | TRU: 697, FAL: 87 | 0.8890306 |
Scale assessing actively open minded thinking about evidence (Pennycook G. Cheyne J. A. Koehler D. & Fugelsang J. A. (2019). On the belief that beliefs should change according to evidence: Implications for conspiratorial moral paranormal political religious and science beliefs.)
Distribution of values for aot_actively_openminded_thinking_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| aot_actively_openminded_thinking_sum | Scale assessing actively open minded thinking about evidence (Pennycook G. Cheyne J. A. Koehler D. & Fugelsang J. A. (2019). On the belief that beliefs should change according to evidence: Implications for conspiratorial moral paranormal political religious and science beliefs.) | numeric | 1486 | 0.1410405 | 22 | 38 | 48 | 37.40164 | 5.934706 | ▂▅▇▇▆ |
The Belief in Conspiracy Theories Inventory (BCTI, Swami et al., 2010) which assessed general conspiracist ideation or belief in conspiracy theories
Distribution of values for bcti_belief_in_conspiracy_sum
1481 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| bcti_belief_in_conspiracy_sum | The Belief in Conspiracy Theories Inventory (BCTI, Swami et al., 2010) which assessed general conspiracist ideation or belief in conspiracy theories | numeric | 1481 | 0.1439306 | 15 | 51 | 129 | 54.04819 | 23.60011 | ▇▇▆▂▁ |
The revised Cognitive Reflection Test (RCRT). The Revised Cognitive Reflection Test originally developed by Toplak West and Stanovich (2014) and subsequently revised by Bronstein Pennycook Bear Rand and Cannon (2019) was used to measure analytic thinking ability.
Distribution of values for crt_analytic_thinking_sum
1236 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| crt_analytic_thinking_sum | The revised Cognitive Reflection Test (RCRT). The Revised Cognitive Reflection Test originally developed by Toplak West and Stanovich (2014) and subsequently revised by Bronstein Pennycook Bear Rand and Cannon (2019) was used to measure analytic thinking ability. | numeric | 1236 | 0.2855491 | 0 | 4 | 7 | 3.953441 | 1.848155 | ▃▃▇▅▆ |
The overclaiming questionnaire adapted from Paulhus et al. (2003).
Distribution of values for ocq_overclaiming_sum
1480 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ocq_overclaiming_sum | The overclaiming questionnaire adapted from Paulhus et al. (2003). | numeric | 1480 | 0.1445087 | 10 | 72 | 143 | 71.516 | 29.66252 | ▃▇▇▆▂ |
The Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014).
Distribution of values for ras_relgious_affliation_sum
1194 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ras_relgious_affliation_sum | The Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). | numeric | 1194 | 0.3098266 | 8 | 21 | 40 | 20.77799 | 8.32119 | ▇▆▇▅▂ |
The rational scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles.
Distribution of values for rei_rational_sum
1235 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| rei_rational_sum | The rational scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. | numeric | 1235 | 0.2861272 | 15 | 52 | 70 | 50.79394 | 10.68324 | ▁▂▅▇▅ |
The experiential scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles.
Distribution of values for rei_experiential_sum
1235 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| rei_experiential_sum | The experiential scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. | numeric | 1235 | 0.2861272 | 16 | 49 | 70 | 48.4101 | 8.768012 | ▁▂▇▇▂ |
Media evaluation task. Awareness sum score for the fake news items
Distribution of values for me_fake_news_awareness_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_fake_news_awareness_sum | Media evaluation task. Awareness sum score for the fake news items | numeric | 1486 | 0.1410405 | 0 | 1 | 6 | 1.413934 | 1.191866 | ▇▃▂▁▁ |
Media evaluation task. Awareness sum score for the real news items
Distribution of values for me_real_news_awareness_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_real_news_awareness_sum | Media evaluation task. Awareness sum score for the real news items | numeric | 1486 | 0.1410405 | 0 | 0 | 4 | 0.2008197 | 0.5178296 | ▇▁▁▁▁ |
Media evaluation task. Accuracy sum score for the fake news items
Distribution of values for me_fake_news_accuracy_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_fake_news_accuracy_sum | Media evaluation task. Accuracy sum score for the fake news items | numeric | 1486 | 0.1410405 | 7 | 17 | 23 | 16.72131 | 2.614497 | ▁▂▇▇▂ |
Media evaluation task. Accuracy sum score for the real news items
Distribution of values for me_real_news_accuracy_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_real_news_accuracy_sum | Media evaluation task. Accuracy sum score for the real news items | numeric | 1486 | 0.1410405 | 6 | 9 | 20 | 9.127049 | 2.460437 | ▇▆▂▁▁ |
Media evaluation task. Sharing sum score for the fake news items
Distribution of values for me_fake_news_sharing_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_fake_news_sharing_sum | Media evaluation task. Sharing sum score for the fake news items | numeric | 1486 | 0.1410405 | 0 | 1 | 6 | 1.561475 | 1.768585 | ▇▂▁▂▁ |
Media evaluation task. Accuracy sum score for the real news items
Distribution of values for me_real_news_sharing_sum
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_real_news_sharing_sum | Media evaluation task. Accuracy sum score for the real news items | numeric | 1486 | 0.1410405 | 0 | 0 | 6 | 0.454918 | 0.9739489 | ▇▁▁▁▁ |
POMP scores derived from scale assessing actively open minded thinking about evidence (Pennycook G. Cheyne J. A. Koehler D. & Fugelsang J. A. (2019). On the belief that beliefs should change according to evidence: Implications for conspiratorial moral paranormal political religious and science beliefs.)
Distribution of values for aot_actively_openminded_thinking_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| aot_actively_openminded_thinking_pomp | POMP scores derived from scale assessing actively open minded thinking about evidence (Pennycook G. Cheyne J. A. Koehler D. & Fugelsang J. A. (2019). On the belief that beliefs should change according to evidence: Implications for conspiratorial moral paranormal political religious and science beliefs.) | numeric | 1486 | 0.1410405 | 35 | 75 | 100 | 73.48361 | 14.87464 | ▂▅▇▇▆ |
POMP scores derived from the Belief in Conspiracy Theories Inventory (BCTI, Swami et al., 2010) which assessed general conspiracist ideation or belief in conspiracy theories
Distribution of values for bcti_belief_in_conspiracy_pomp
1481 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| bcti_belief_in_conspiracy_pomp | POMP scores derived from the Belief in Conspiracy Theories Inventory (BCTI, Swami et al., 2010) which assessed general conspiracist ideation or belief in conspiracy theories | numeric | 1481 | 0.1439306 | 0 | 30 | 95 | 32.56627 | 19.67961 | ▇▇▆▂▁ |
POMP scores derived from revised Cognitive Reflection Test (RCRT). The Revised Cognitive Reflection Test originally developed by Toplak West and Stanovich (2014) and subsequently revised by Bronstein Pennycook Bear Rand and Cannon (2019) was used to measure analytic thinking ability.
Distribution of values for crt_analytic_thinking_pomp
1236 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| crt_analytic_thinking_pomp | POMP scores derived from revised Cognitive Reflection Test (RCRT). The Revised Cognitive Reflection Test originally developed by Toplak West and Stanovich (2014) and subsequently revised by Bronstein Pennycook Bear Rand and Cannon (2019) was used to measure analytic thinking ability. | numeric | 1236 | 0.2855491 | 0 | 57 | 100 | 56.47368 | 26.39254 | ▃▃▇▅▆ |
POMP scores derived from the overclaiming questionnaire adapted from Paulhus et al. (2003).
Distribution of values for ocq_overclaiming_pomp
1480 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ocq_overclaiming_pomp | POMP scores derived from the overclaiming questionnaire adapted from Paulhus et al. (2003). | numeric | 1480 | 0.1445087 | 6 | 40 | 79 | 39.728 | 16.45628 | ▃▇▇▆▂ |
POMP scores derived from the Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014).
Distribution of values for ras_relgious_affliation_pomp
1194 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| ras_relgious_affliation_pomp | POMP scores derived from the Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). | numeric | 1194 | 0.3098266 | 0 | 41 | 100 | 39.91978 | 26.0168 | ▇▆▇▅▂ |
POMP scores for the rational scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles.
Distribution of values for rei_rational_pomp
1235 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| rei_rational_pomp | POMP scores for the rational scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. | numeric | 1235 | 0.2861272 | -4 | 27 | 42 | 25.67879 | 8.894561 | ▁▂▅▇▅ |
POMP scores for the experiential scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles.
Distribution of values for rei_experiential_pomp
1235 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| rei_experiential_pomp | POMP scores for the experiential scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. | numeric | 1235 | 0.2861272 | -3 | 24 | 42 | 23.68687 | 7.323976 | ▁▂▇▇▂ |
Media evaluation task. POMP score for the fake news items (awareness)
Distribution of values for me_fake_news_awareness_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_fake_news_awareness_pomp | Media evaluation task. POMP score for the fake news items (awareness) | numeric | 1486 | 0.1410405 | -50 | -46 | -25 | -44.29508 | 4.888364 | ▇▃▂▁▁ |
Media evaluation task. POMP score for the real news items (awareness)
Distribution of values for me_real_news_awareness_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_real_news_awareness_pomp | Media evaluation task. POMP score for the real news items (awareness) | numeric | 1486 | 0.1410405 | -50 | -50 | -33 | -49.19262 | 2.102269 | ▇▁▁▁▁ |
Media evaluation task. POMP score for the fake news items (accuracy)
Distribution of values for me_fake_news_accuracy_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_fake_news_accuracy_pomp | Media evaluation task. POMP score for the fake news items (accuracy) | numeric | 1486 | 0.1410405 | -14 | 14 | 31 | 13.11475 | 7.217602 | ▁▂▆▇▁ |
Media evaluation task. POMP score for the real news items (accuracy)
Distribution of values for me_real_news_accuracy_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_real_news_accuracy_pomp | Media evaluation task. POMP score for the real news items (accuracy) | numeric | 1486 | 0.1410405 | -17 | -8 | 22 | -8.032787 | 6.895379 | ▇▆▂▁▁ |
Media evaluation task. POMP score for the fake news items (sharing)
Distribution of values for me_fake_news_sharing_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_fake_news_sharing_pomp | Media evaluation task. POMP score for the fake news items (sharing) | numeric | 1486 | 0.1410405 | -50 | -46 | -25 | -43.57787 | 7.389103 | ▇▂▁▂▁ |
Media evaluation task. POMP score for the real news items (sharing)
Distribution of values for me_real_news_sharing_pomp
1486 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| me_real_news_sharing_pomp | Media evaluation task. POMP score for the real news items (sharing) | numeric | 1486 | 0.1410405 | -50 | -50 | -25 | -48.15984 | 3.989062 | ▇▁▁▁▁ |
IAT_D2 recoded for source_valence. If source_valence == “negative”, IAT_D2*-1, otherwise IAT_D2.
Distribution of values for IAT_D2_recoded_for_source_valence
141 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| IAT_D2_recoded_for_source_valence | IAT_D2 recoded for source_valence. If source_valence == “negative”, IAT_D2*-1, otherwise IAT_D2. | numeric | 141 | 0.9184971 | -0.94 | 0.2 | 1.6 | 0.1854097 | 0.3764714 | ▁▅▇▃▁ |
mean_self_reported_evaluation recoded for source_valence. If source_valence == “negative”, mean_self_reported_evaluation*-1, otherwise mean_self_reported_evaluation.
Distribution of values for mean_self_reported_evaluation_recoded_for_source_valence
98 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| mean_self_reported_evaluation_recoded_for_source_valence | mean_self_reported_evaluation recoded for source_valence. If source_valence == “negative”, mean_self_reported_evaluation*-1, otherwise mean_self_reported_evaluation. | numeric | 98 | 0.9433526 | -3 | 2 | 3 | 1.568836 | 1.289025 | ▁▁▂▃▇ |
mean_intentions recoded for source_valence. If source_valence == “negative”, mean_intentions*-1, otherwise mean_intentions.
Distribution of values for mean_intentions_recoded_for_source_valence
1485 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| mean_intentions_recoded_for_source_valence | mean_intentions recoded for source_valence. If source_valence == “negative”, mean_intentions*-1, otherwise mean_intentions. | numeric | 1485 | 0.1416185 | -2 | 0.67 | 2 | 0.5263673 | 1.298441 | ▂▃▅▂▇ |
Question assessin if participants were aware of the concept of Deepfaking before taking part in the study
Distribution of values for deepfake_concept_check
1294 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| deepfake_concept_check | Question assessin if participants were aware of the concept of Deepfaking before taking part in the study | logical | 1294 | 0.2520231 | TRU: 234, FAL: 202 | 0.5366972 |
Ratings indicating whether a participant detected that they were exposed to Deepfaked content during the study. Ratings obtained from Rater 1
Distribution of values for deepfake_detected_rater_1
1120 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| deepfake_detected_rater_1 | Ratings indicating whether a participant detected that they were exposed to Deepfaked content during the study. Ratings obtained from Rater 1 | logical | 1120 | 0.3526012 | FAL: 462, TRU: 148 | 0.242623 |
Ratings indicating whether a participant detected that they were exposed to Deepfaked content during the study. Ratings obtained from Rater 2
Distribution of values for deepfake_detected_rater_2
1120 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| deepfake_detected_rater_2 | Ratings indicating whether a participant detected that they were exposed to Deepfaked content during the study. Ratings obtained from Rater 2 | logical | 1120 | 0.3526012 | FAL: 476, TRU: 134 | 0.2196721 |
Ratings indicating if participants were aware of the concept of a Deepfake before taking part in the study. Ratings obtained from Rater 1
Distribution of values for deepfake_concept_check_rater_1
1294 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| deepfake_concept_check_rater_1 | Ratings indicating if participants were aware of the concept of a Deepfake before taking part in the study. Ratings obtained from Rater 1 | logical | 1294 | 0.2520231 | TRU: 247, FAL: 189 | 0.5665138 |
Ratings indicating if participants were aware of the concept of a Deepfake before taking part in the study. Ratings obtained from Rater 2
Distribution of values for deepfake_concept_check_rater_2
1294 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| deepfake_concept_check_rater_2 | Ratings indicating if participants were aware of the concept of a Deepfake before taking part in the study. Ratings obtained from Rater 2 | logical | 1294 | 0.2520231 | TRU: 247, FAL: 189 | 0.5665138 |
Open ended gender
Distribution of values for gender_self_describe
1725 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| gender_self_describe | Open ended gender | character | 1725 | 0.0028902 | 1 | 0 | 4 | 4 | 0 |
Ethnicity
Distribution of values for ethnicity
1189 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| ethnicity | Ethnicity | character | 1189 | 0.3127168 | 7 | 0 | 5 | 25 | 0 |
Open ended ethnicity
Distribution of values for ethnicity_self_describe
1701 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| ethnicity_self_describe | Open ended ethnicity | character | 1701 | 0.016763 | 19 | 0 | 4 | 40 | 0 |
Location
Distribution of values for location
1190 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| location | Location | character | 1190 | 0.3121387 | 18 | 0 | 5 | 24 | 0 |
Education
Distribution of values for education
1189 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| education | Education | character | 1189 | 0.3127168 | 8 | 0 | 7 | 21 | 0 |
Employment status
Distribution of values for employment
1189 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| employment | Employment status | character | 1189 | 0.3127168 | 10 | 0 | 7 | 24 | 0 |
Education recoded into seven groups
Distribution of values for education_recoded
1189 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| education_recoded | Education recoded into seven groups | numeric | 1189 | 0.3127168 | 1 | 5 | 7 | 4.072089 | 1.526427 | ▅▅▁▇▃ |
Income level
Distribution of values for income
1190 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| income | Income level | character | 1190 | 0.3121387 | 10 | 0 | 12 | 20 | 0 |
Income level recoded into 7 groups
Distribution of values for income_recoded
1238 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| income_recoded | Income level recoded into 7 groups | numeric | 1238 | 0.2843931 | 1 | 3 | 8 | 2.943089 | 1.503835 | ▇▆▇▁▁ |
4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about the importance of political ideology to one’s self-identity
Distribution of values for political_ideology_identity
1190 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| political_ideology_identity | 4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about the importance of political ideology to one’s self-identity | numeric | 1190 | 0.3121387 | -3 | 1 | 3 | 0.8574074 | 1.544648 | ▂▂▃▇▇ |
4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about how liberal vs. conservative they are when it comes to economic issues.
Distribution of values for political_ideology_economic_issues
1190 missing values.
| name | label | data_type | n_missing | complete_rate | min | median | max | mean | sd | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| political_ideology_economic_issues | 4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about how liberal vs. conservative they are when it comes to economic issues. | numeric | 1190 | 0.3121387 | -2 | 0 | 2 | -0.4148148 | 1.032929 | ▃▇▇▃▁ |
Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). Raw responses
Distribution of values for religious_affiliation_general
1190 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| religious_affiliation_general | Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). Raw responses | character | 1190 | 0.3121387 | 10 | 0 | 4 | 16 | 0 |
Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). Participants categorised into one of three groups (Agnostic Atheist Religious)
Distribution of values for religious_affiliation_general_recoded
1190 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| religious_affiliation_general_recoded | Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). Participants categorised into one of three groups (Agnostic Atheist Religious) | character | 1190 | 0.3121387 | 3 | 0 | 7 | 9 | 0 |
Mark participants for exclusion if their total error rate is >30% their error rate in any one block is >40% or if >10% RTs are <300ms.
Distribution of values for passed_iat_performance
122 missing values.
| name | label | data_type | n_missing | complete_rate | count | mean |
|---|---|---|---|---|---|---|
| passed_iat_performance | Mark participants for exclusion if their total error rate is >30% their error rate in any one block is >40% or if >10% RTs are <300ms. | logical | 122 | 0.9294798 | TRU: 1440, FAL: 168 | 0.8955224 |
Complete IAT data (used for exclusions)
Distribution of values for complete_iat
122 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| complete_iat | Complete IAT data (used for exclusions) | character | 122 | 0.9294798 | 3 | 0 | 6 | 8 | 0 |
Complete self reported evaluations data (used for exclusions)
Distribution of values for complete_selfreport
98 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| complete_selfreport | Complete self reported evaluations data (used for exclusions) | character | 98 | 0.9433526 | 2 | 0 | 6 | 8 | 0 |
Complete behavioural intentions data (used for exclusions)
Distribution of values for complete_intentions
1485 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| complete_intentions | Complete behavioural intentions data (used for exclusions) | character | 1485 | 0.1416185 | 2 | 0 | 6 | 8 | 0 |
Did the particiapant complete the self-reported evaluations or the IAT first?
Distribution of values for task_order
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| task_order | Did the particiapant complete the self-reported evaluations or the IAT first? | character | 0 | 1 | 2 | 0 | 9 | 25 | 0 |
Was the participant exposed to the intervention-consistent or intervention-inconsistent block in the IAT first? E.g. if source_valence was negative did the IAT map Chris and negative to the same key (con) or Chris and positive (incon)?
Distribution of values for iat_block_order
0 missing values.
| name | label | data_type | n_missing | complete_rate | n_unique | empty | min | max | whitespace |
|---|---|---|---|---|---|---|---|---|---|
| iat_block_order | Was the participant exposed to the intervention-consistent or intervention-inconsistent block in the IAT first? E.g. if source_valence was negative did the IAT map Chris and negative to the same key (con) or Chris and positive (incon)? | character | 0 | 1 | 2 | 0 | 31 | 33 | 0 |
JSON-LD metadata
The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.
{
"name": ".",
"datePublished": "2020-11-15",
"description": "The dataset has N=1730 rows and 76 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
"keywords": ["subject", "experiment", "intervention_medium", "source_valence", "experiment_condition", "exclude_subject", "exclude_implausible_intervention_linger", "intervention_linger_minutes", "age", "gender", "IAT_D2", "mean_self_reported_evaluation", "mean_intentions", "deepfake_detected", "ratings_bad_good", "ratings_dislike_like", "ratings_negative_positive", "diagnosticity", "demand", "reactance", "hypothesis_awareness", "influence_awareness", "aot_actively_openminded_thinking_sum", "bcti_belief_in_conspiracy_sum", "crt_analytic_thinking_sum", "ocq_overclaiming_sum", "ras_relgious_affliation_sum", "rei_rational_sum", "rei_experiential_sum", "me_fake_news_awareness_sum", "me_real_news_awareness_sum", "me_fake_news_accuracy_sum", "me_real_news_accuracy_sum", "me_fake_news_sharing_sum", "me_real_news_sharing_sum", "aot_actively_openminded_thinking_pomp", "bcti_belief_in_conspiracy_pomp", "crt_analytic_thinking_pomp", "ocq_overclaiming_pomp", "ras_relgious_affliation_pomp", "rei_rational_pomp", "rei_experiential_pomp", "me_fake_news_awareness_pomp", "me_real_news_awareness_pomp", "me_fake_news_accuracy_pomp", "me_real_news_accuracy_pomp", "me_fake_news_sharing_pomp", "me_real_news_sharing_pomp", "IAT_D2_recoded_for_source_valence", "mean_self_reported_evaluation_recoded_for_source_valence", "mean_intentions_recoded_for_source_valence", "deepfake_concept_check", "deepfake_detected_rater_1", "deepfake_detected_rater_2", "deepfake_concept_check_rater_1", "deepfake_concept_check_rater_2", "gender_self_describe", "ethnicity", "ethnicity_self_describe", "location", "education", "employment", "education_recoded", "income", "income_recoded", "political_ideology_identity", "political_ideology_social_issues", "political_ideology_economic_issues", "religious_affiliation_general", "religious_affiliation_general_recoded", "passed_iat_performance", "complete_iat", "complete_selfreport", "complete_intentions", "task_order", "iat_block_order"],
"@context": "http://schema.org/",
"@type": "Dataset",
"variableMeasured": [
{
"name": "subject",
"description": "Unique subject identifier",
"@type": "propertyValue"
},
{
"name": "experiment",
"description": "Experiment data was collected as part of",
"@type": "propertyValue"
},
{
"name": "intervention_medium",
"description": "What medium did the intervention (whether deepfaked or genuine) take (e.g. video and audio vs just audio)",
"@type": "propertyValue"
},
{
"name": "source_valence",
"description": "What was the researcher-intended valence of the intervention? I.e. was the participant exposed to positive or negative messages?",
"@type": "propertyValue"
},
{
"name": "experiment_condition",
"description": "Was the intervention genuine or deepfaked content?",
"@type": "propertyValue"
},
{
"name": "exclude_subject",
"description": "Should the participant be excluded (TRUE) or retained (FALSE) based on passed_iat_performance complete_iat complete_selfreport and complete_intentions",
"@type": "propertyValue"
},
{
"name": "exclude_implausible_intervention_linger",
"description": "Should the participant be excluded (TRUE) or retained (FALSE) based on them spending not enough time (<1.5 minutes or too much time (>4.5 minutes) on the page that delivered the audio/video intervention.",
"@type": "propertyValue"
},
{
"name": "intervention_linger_minutes",
"description": "Number of minutes spent viewing the page that delivered the intervention.",
"@type": "propertyValue"
},
{
"name": "age",
"description": "Participant age",
"@type": "propertyValue"
},
{
"name": "gender",
"description": "Participant gender",
"@type": "propertyValue"
},
{
"name": "IAT_D2",
"description": "The IAT captures automatic evaluations of Chris the character depicted in the intervention. Accuracies and reaction times on IAT were converted to D2 scores following Greenwald et al 2003 and implemented using the IATScores R package. Briefly D2 is a standardized difference score of trimmed reaction times in one block type versus the other: (mean_block_2 - mean_block_1) / standard_deviation_all_blocks",
"@type": "propertyValue"
},
{
"name": "mean_self_reported_evaluation",
"description": "Mean self-reported evaluation (positive-negative good-bad pleasant-unpleasant) of Chris the character depicted in the intervention.",
"@type": "propertyValue"
},
{
"name": "mean_intentions",
"description": "Mean behavioural intentions",
"@type": "propertyValue"
},
{
"name": "deepfake_detected",
"description": "Open ended responses to the deepfaking detection question were hand scored by two independent reviewers (see \"3 Instructions for raters.docx\"). If both reviewers scored an open ended response as having detected the intervention as a deepfake (whether correctly or not), this variable was set to TRUE. Otherwise FALSE.",
"@type": "propertyValue"
},
{
"name": "ratings_bad_good",
"description": "Item level data for self report ratings scale item 1, bad vs good",
"@type": "propertyValue"
},
{
"name": "ratings_dislike_like",
"description": "Item level data for self report ratings scale item 1, dislike vs like",
"@type": "propertyValue"
},
{
"name": "ratings_negative_positive",
"description": "Item level data for self report ratings scale item 1, negative vs positive",
"@type": "propertyValue"
},
{
"name": "diagnosticity",
"description": "Question assessing whether people believe that the targets actions in the video/audio were representative of his 'true' character",
"@type": "propertyValue"
},
{
"name": "demand",
"description": "Assesssment of whether evaluations of the targer reflected how the person genuinely felt or if they simply responded in a way they thought the researchers wanted them to.",
"@type": "propertyValue"
},
{
"name": "reactance",
"description": "Assesssment of whether evaluations of the targer reflected how the person genuinely felt or if they responded in the opposite way than they thought the researchers wanted them to.",
"@type": "propertyValue"
},
{
"name": "hypothesis_awareness",
"description": "Question asking what participants thought the experiment was about (i.e. what the experimenter's agenda was in the study)",
"@type": "propertyValue"
},
{
"name": "influence_awareness",
"description": "Question asking if participants thought the video/audio influenced how much they liked or disliked the target",
"@type": "propertyValue"
},
{
"name": "aot_actively_openminded_thinking_sum",
"description": "Scale assessing actively open minded thinking about evidence (Pennycook G. Cheyne J. A. Koehler D. & Fugelsang J. A. (2019). On the belief that beliefs should change according to evidence: Implications for conspiratorial moral paranormal political religious and science beliefs.)",
"@type": "propertyValue"
},
{
"name": "bcti_belief_in_conspiracy_sum",
"description": "The Belief in Conspiracy Theories Inventory (BCTI, Swami et al., 2010) which assessed general conspiracist ideation or belief in conspiracy theories ",
"@type": "propertyValue"
},
{
"name": "crt_analytic_thinking_sum",
"description": "The revised Cognitive Reflection Test (RCRT). The Revised Cognitive Reflection Test originally developed by Toplak West and Stanovich (2014) and subsequently revised by Bronstein Pennycook Bear Rand and Cannon (2019) was used to measure analytic thinking ability. ",
"@type": "propertyValue"
},
{
"name": "ocq_overclaiming_sum",
"description": "The overclaiming questionnaire adapted from Paulhus et al. (2003). ",
"@type": "propertyValue"
},
{
"name": "ras_relgious_affliation_sum",
"description": "The Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). ",
"@type": "propertyValue"
},
{
"name": "rei_rational_sum",
"description": "The rational scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. ",
"@type": "propertyValue"
},
{
"name": "rei_experiential_sum",
"description": "The experiential scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. ",
"@type": "propertyValue"
},
{
"name": "me_fake_news_awareness_sum",
"description": "Media evaluation task. Awareness sum score for the fake news items",
"@type": "propertyValue"
},
{
"name": "me_real_news_awareness_sum",
"description": "Media evaluation task. Awareness sum score for the real news items",
"@type": "propertyValue"
},
{
"name": "me_fake_news_accuracy_sum",
"description": "Media evaluation task. Accuracy sum score for the fake news items",
"@type": "propertyValue"
},
{
"name": "me_real_news_accuracy_sum",
"description": "Media evaluation task. Accuracy sum score for the real news items",
"@type": "propertyValue"
},
{
"name": "me_fake_news_sharing_sum",
"description": "Media evaluation task. Sharing sum score for the fake news items",
"@type": "propertyValue"
},
{
"name": "me_real_news_sharing_sum",
"description": "Media evaluation task. Accuracy sum score for the real news items",
"@type": "propertyValue"
},
{
"name": "aot_actively_openminded_thinking_pomp",
"description": "POMP scores derived from scale assessing actively open minded thinking about evidence (Pennycook G. Cheyne J. A. Koehler D. & Fugelsang J. A. (2019). On the belief that beliefs should change according to evidence: Implications for conspiratorial moral paranormal political religious and science beliefs.)",
"@type": "propertyValue"
},
{
"name": "bcti_belief_in_conspiracy_pomp",
"description": "POMP scores derived from the Belief in Conspiracy Theories Inventory (BCTI, Swami et al., 2010) which assessed general conspiracist ideation or belief in conspiracy theories ",
"@type": "propertyValue"
},
{
"name": "crt_analytic_thinking_pomp",
"description": "POMP scores derived from revised Cognitive Reflection Test (RCRT). The Revised Cognitive Reflection Test originally developed by Toplak West and Stanovich (2014) and subsequently revised by Bronstein Pennycook Bear Rand and Cannon (2019) was used to measure analytic thinking ability. ",
"@type": "propertyValue"
},
{
"name": "ocq_overclaiming_pomp",
"description": "POMP scores derived from the overclaiming questionnaire adapted from Paulhus et al. (2003). ",
"@type": "propertyValue"
},
{
"name": "ras_relgious_affliation_pomp",
"description": "POMP scores derived from the Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). ",
"@type": "propertyValue"
},
{
"name": "rei_rational_pomp",
"description": "POMP scores for the rational scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. ",
"@type": "propertyValue"
},
{
"name": "rei_experiential_pomp",
"description": "POMP scores for the experiential scale. Derived from the Rational-Experiential Inventory (REI) developed by Pacini and Epstein (1999) designed to measure individual differences in processing styles. ",
"@type": "propertyValue"
},
{
"name": "me_fake_news_awareness_pomp",
"description": "Media evaluation task. POMP score for the fake news items (awareness)",
"@type": "propertyValue"
},
{
"name": "me_real_news_awareness_pomp",
"description": "Media evaluation task. POMP score for the real news items (awareness)",
"@type": "propertyValue"
},
{
"name": "me_fake_news_accuracy_pomp",
"description": "Media evaluation task. POMP score for the fake news items (accuracy)",
"@type": "propertyValue"
},
{
"name": "me_real_news_accuracy_pomp",
"description": "Media evaluation task. POMP score for the real news items (accuracy)",
"@type": "propertyValue"
},
{
"name": "me_fake_news_sharing_pomp",
"description": "Media evaluation task. POMP score for the fake news items (sharing)",
"@type": "propertyValue"
},
{
"name": "me_real_news_sharing_pomp",
"description": "Media evaluation task. POMP score for the real news items (sharing)",
"@type": "propertyValue"
},
{
"name": "IAT_D2_recoded_for_source_valence",
"description": "IAT_D2 recoded for source_valence. If source_valence == \"negative\", IAT_D2*-1, otherwise IAT_D2.",
"@type": "propertyValue"
},
{
"name": "mean_self_reported_evaluation_recoded_for_source_valence",
"description": "mean_self_reported_evaluation recoded for source_valence. If source_valence == \"negative\", mean_self_reported_evaluation*-1, otherwise mean_self_reported_evaluation.",
"@type": "propertyValue"
},
{
"name": "mean_intentions_recoded_for_source_valence",
"description": "mean_intentions recoded for source_valence. If source_valence == \"negative\", mean_intentions*-1, otherwise mean_intentions.",
"@type": "propertyValue"
},
{
"name": "deepfake_concept_check",
"description": "Question assessin if participants were aware of the concept of Deepfaking before taking part in the study",
"@type": "propertyValue"
},
{
"name": "deepfake_detected_rater_1",
"description": "Ratings indicating whether a participant detected that they were exposed to Deepfaked content during the study. Ratings obtained from Rater 1",
"@type": "propertyValue"
},
{
"name": "deepfake_detected_rater_2",
"description": "Ratings indicating whether a participant detected that they were exposed to Deepfaked content during the study. Ratings obtained from Rater 2",
"@type": "propertyValue"
},
{
"name": "deepfake_concept_check_rater_1",
"description": "Ratings indicating if participants were aware of the concept of a Deepfake before taking part in the study. Ratings obtained from Rater 1",
"@type": "propertyValue"
},
{
"name": "deepfake_concept_check_rater_2",
"description": "Ratings indicating if participants were aware of the concept of a Deepfake before taking part in the study. Ratings obtained from Rater 2",
"@type": "propertyValue"
},
{
"name": "gender_self_describe",
"description": "Open ended gender",
"@type": "propertyValue"
},
{
"name": "ethnicity",
"description": "Ethnicity",
"@type": "propertyValue"
},
{
"name": "ethnicity_self_describe",
"description": "Open ended ethnicity",
"@type": "propertyValue"
},
{
"name": "location",
"description": "Location",
"@type": "propertyValue"
},
{
"name": "education",
"description": "Education",
"@type": "propertyValue"
},
{
"name": "employment",
"description": "Employment status",
"@type": "propertyValue"
},
{
"name": "education_recoded",
"description": "Education recoded into seven groups",
"@type": "propertyValue"
},
{
"name": "income",
"description": "Income level",
"@type": "propertyValue"
},
{
"name": "income_recoded",
"description": "Income level recoded into 7 groups",
"@type": "propertyValue"
},
{
"name": "political_ideology_identity",
"description": "4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about the importance of political ideology to one's self-identity",
"@type": "propertyValue"
},
{
"name": "political_ideology_social_issues",
"description": "4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about how liberal vs. conservative they are when it comes to social issues.",
"@type": "propertyValue"
},
{
"name": "political_ideology_economic_issues",
"description": "4 item-measure of political ideology developed by Pennycook and Rand (2018). This measure combines the two questions about how liberal vs. conservative they are when it comes to economic issues.",
"@type": "propertyValue"
},
{
"name": "religious_affiliation_general",
"description": "Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). Raw responses",
"@type": "propertyValue"
},
{
"name": "religious_affiliation_general_recoded",
"description": "Religious Affiliation Scale (Pennycook Cheyne Barr Koehler & Fugelsang 2014). Participants categorised into one of three groups (Agnostic Atheist Religious)",
"@type": "propertyValue"
},
{
"name": "passed_iat_performance",
"description": "Mark participants for exclusion if their total error rate is >30% their error rate in any one block is >40% or if >10% RTs are <300ms.",
"@type": "propertyValue"
},
{
"name": "complete_iat",
"description": "Complete IAT data (used for exclusions)",
"@type": "propertyValue"
},
{
"name": "complete_selfreport",
"description": "Complete self reported evaluations data (used for exclusions)",
"@type": "propertyValue"
},
{
"name": "complete_intentions",
"description": "Complete behavioural intentions data (used for exclusions)",
"@type": "propertyValue"
},
{
"name": "task_order",
"description": "Did the particiapant complete the self-reported evaluations or the IAT first?",
"@type": "propertyValue"
},
{
"name": "iat_block_order",
"description": "Was the participant exposed to the intervention-consistent or intervention-inconsistent block in the IAT first? E.g. if source_valence was negative did the IAT map Chris and negative to the same key (con) or Chris and positive (incon)?",
"@type": "propertyValue"
}
]
}`Original csv file is used for analyses (as it is simplest), but other file types that integrate the labels are likely to be more useful for reuse.
I include an R .rds file (which includes data labels and data types), SPSS .sav and Stata .dta files.
## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_IE.UTF-8/en_IE.UTF-8/en_IE.UTF-8/C/en_IE.UTF-8/en_IE.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] rio_0.5.16 labelled_2.7.0 codebook_0.9.2 kableExtra_1.3.1
## [5] knitr_1.30 forcats_0.5.0 stringr_1.4.0 dplyr_1.0.2
## [9] purrr_0.3.4 readr_1.3.1 tidyr_1.1.2 tibble_3.0.3
## [13] ggplot2_3.3.2 tidyverse_1.3.0
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.1 jsonlite_1.7.1 viridisLite_0.3.0 modelr_0.1.8
## [5] assertthat_0.2.1 highr_0.8 cellranger_1.1.0 yaml_2.2.1
## [9] globals_0.13.1 pillar_1.4.6 backports_1.1.9 glue_1.4.2
## [13] digest_0.6.25 rvest_0.3.5 colorspace_1.4-1 htmltools_0.5.0
## [17] pkgconfig_2.0.3 broom_0.7.2 listenv_0.8.0 haven_2.3.1
## [21] scales_1.1.1 webshot_0.5.2 openxlsx_4.1.5 generics_0.0.2
## [25] farver_2.0.3 ellipsis_0.3.1 DT_0.13 withr_2.2.0
## [29] repr_1.1.0 skimr_2.1.2 cli_2.0.2 rmdpartials_0.5.8
## [33] magrittr_1.5 crayon_1.3.4 readxl_1.3.1 evaluate_0.14
## [37] fs_1.4.1 future_1.19.1 fansi_0.4.1 xml2_1.3.2
## [41] foreign_0.8-80 tools_4.0.2 data.table_1.13.2 hms_0.5.3
## [45] lifecycle_0.2.0 munsell_0.5.0 reprex_0.3.0 zip_2.1.1
## [49] compiler_4.0.2 rlang_0.4.8 grid_4.0.2 rstudioapi_0.11
## [53] htmlwidgets_1.5.1 crosstalk_1.1.0.1 base64enc_0.1-3 labeling_0.3
## [57] rmarkdown_2.5 gtable_0.3.0 codetools_0.2-16 DBI_1.1.0
## [61] curl_4.3 R6_2.4.1 lubridate_1.7.9 stringi_1.4.6
## [65] parallel_4.0.2 Rcpp_1.0.5 vctrs_0.3.4 dbplyr_1.4.3
## [69] tidyselect_1.1.0 xfun_0.19